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(12) United States Patent (10) Patent No.: US 8.473450 B2 Bakalash Et Al

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(12) United States Patent (10) Patent No.: US 8.473450 B2 Bakalash Et Al USOO847345OB2 (12) United States Patent (10) Patent No.: US 8.473450 B2 Bakalash et al. (45) Date of Patent: *Jun. 25, 2013 (54) RELATIONAL DATABASE MANAGEMENT (52) U.S. Cl. SYSTEM (RDBMS) EMPLOYING USPC ........................................... 707/600; 707/770 MULTI-DIMENSIONAL DATABASE (MDDB) (58) Field of Classification Search FOR SERVICING QUERY STATEMENTS None THROUGHONE ORMORE CLIENT See application file for complete search history. MACHINES (56) References Cited (75) Inventors: Reuven Bakalash, Beer Sheva (IL); Guy U.S. PATENT DOCUMENTS Shaked, Shdema (IL); Joseph Caspi, 4,590,465. A 5, 1986 Fuchs Herzlyia (IL) 4,598.400 A 7, 1986 Hillis (73) Assignee: Yanicklo Technology Limited Liability (Continued) Company, Wilmington, DE (US) FOREIGN PATENT DOCUMENTS (*) Notice: Subject to any disclaimer, the term of this EP O 314 279 5, 1989 patent is extended or adjusted under 35 EP O 657 052 6, 1995 U.S.C. 154(b) by 13 days. (Continued) OTHER PUBLICATIONS This patent is Subject to a terminal dis claimer. Scheuermann, P. J. Shim and R. Vingralek “WATCHMAN: A Data Warehouse Intelligent Cache Manager'. Proceedings of the 22nd International Conference on Very Large Databases (VLDB), 1996, (21) Appl. No.: 12/455,665 pp. 51-62.* (22) Filed: Jun. 4, 2009 (Continued) (65) Prior Publication Data Primary Examiner — Robert Timblin (74) Attorney, Agent, or Firm — Knobbe, Martens, Olson & US 2009/027641.0 A1 Nov. 5, 2009 Bear LLP Related U.S. Application Data (57) ABSTRACT A relational database management system (RDBMS) for ser (63) Continuation of application No. 1 1/888,904, filed on vicing query statements through one or more client machines. Aug. 2, 2007, now abandoned, which is a continuation The RDBMS comprises a query interface adapted to receive of application No. 10/839,782, filed on May 5, 2004, query statements from the client machines. The query han now abandoned, which is a continuation of application dling mechanism (i) receives each request from the query No. 10/314,884, filed on Dec. 9, 2002, now Pat. No. interface, (ii) extracts a set of dimensions associated with the 7.315,849, which is a continuation of application No. request, (iii) uses the dimensions to retrieve aggregated fact data from a multi-dimensional database (MDDB), and (iv) 09/796,098, filed on Feb. 28, 2001, now abandoned, forwards retrieved aggregated fact data to the query process which is a continuation-in-part of application No. ing mechanism for Subsequent processing. When the query 09/514,611, filed on Feb. 28, 2000, now Pat. No. processing mechanism determines that servicing of one or 6,434.544, and a continuation-in-part of application more query requests require data stored in the relational No. 09/634,748, filed on Aug. 9, 2000, now Pat. No. tables, then the query processing mechanism automatically 6,385,604. routes the requests to the relational data tables, so that data can be accessed from the relational tables and forwarded to (51) Int. Cl. the query processing mechanism for use in servicing the G06F 7/30 (2006.01) requests, in a manner transparent to the client machine. G06F 7700 (2006.01) 20 Claims, 50 Drawing Sheets DAAWAREHOUSERDBMS - - -SUPPORMCHANISMS - - - - - - - - - - - - - - MACNE D AGGREGAON META-AA STORE MODULE (DICTIONARY) ANALYCA ProcessNG ANDU UERYAN ENERPRISE RELAONAL REPORING OAP US 8,473.450 B2 Page 2 U.S. PATENT DOCUMENTS 5,978,788 A 11/1999 Castelli et al. 4,641.351 A 2f1987 Preston, Jr. E. A 2. tly al. 4,685,144. A 8/1987 McCubbrey et al. 5.990.802 A 1/1999 it al. 4,814,980 A 3, 1989 Peterson et al. 5.99.1754 A 11/1999 Raitto et all 4.985.834.4,868,733. A 9/19891, 1991 C1Fujisawa 1et al. 5.999,192- - - A 12/1999 Selfridge et al. 4985.856 A 1, 1991 kNG, a 6,003,024. A 12/1999 Bair et al. 4987,554 A 1, 1991 Ae 6,003,029 A 12/1999 Agrawal et al. 4,989,141 A 1/1991 Lyons et al. 6,003,036 A 12/1999 Martin 5.095,427 A 3, 1992 Tanaka et all 6,006,216 A 12/1999 Griffin et al. 5.101.475 A 3/1992 Kaufman et al. GA 'i G. Anne a 5,189.608 A 2/1993 Lyons et al. 6,033695 A 2.2000 Osbornet al. 5,197,005 A * 3/1993 Shwartz et al. ........ 707,999.OO2 W4 - 5,202.985. A 4, 1993 Goval 6,034,697 A 3/2000 Becker 5.222.26 A 6, 1993 E. 1 6,041,103 A 3/2000 LaPorta et al. 5.222.37 A 6, 1993 E. et al. 6,047.323 A * 4/2000 Krause .......................... 709,227 5,257,365 A 10/1993 Powers et al. 92 A 38 Pla 1 5,278,966 A 1/1994 Parks et al. 82. A : \etal. 5,280.474. A 1/1994 Nickolls et al. aw sy 5,293.615 A 3, 1994 Amada 6,078,924 A 6/2000 Ainsbury et al. 5,297.2805,297.265 A 3,3/1994 1994 FranketPotts, Sr. al. et all 822.W-1 A $398 Rgrawal all etetal al. 5,299.321 A 3, 1994 Lizuka 6,108,647 A 8, 2000 Poosala et al. 5,307.484 A 4/1994 Baker et al. 6,115,705. A 9/2000 Larson 5.359.724. A 10, 1994 Earl 6,115,714 A 9/2000 Gallagher et al. 5.361.385 A 1/1994 Bilash 6,122,628 A 9, 2000 Castelli et al. 5,379.419 A 1/1995 Heffernan et al. ES A 858 Matty et al. 5,381,518. A 1/1995 Drebin et al. 6.134,541. A 10 2000 Castellietal 5,386,556 A * 1/1995 Hedin et al. ........... TO7 (999-004 6.141655. A 10/2000 Johnsonetal 5,404,506 A 4/1995 Fujisawa et al. 6.151584 A 11/2000 Papierniak tal 5,410,693. A 4, 1995 Yu et al. k - J. apierniak et al. 5.519859 A 5, 1996 Grace 6,151,601 A 11/2000 Papierniak et al. 5,553,226 A 9/1996 Kiuchi et al. 838. A 338 R. 5,555.408 A 9/1996 Fujisawa et al. J. W. J. 5,696,916 A 12/1997 Yamazaki etal 6,163,774. A 12/2000 Lore et al. 5.706503.5,706,495 A 1,1/1998 1998 ChadhaP ettal al. 6,173,310$16.3% B1A, 1229991/2001 Yostlokken et al. ..................... TO9,201 5.731910 A 2, 1998 E. 6,182,060 B1 1/2001 Hedgcock et al. 5.742,806 A 4, 1998 RA 6,182,061 B1 1/2001 Matsuzawa et al. 5,745,764 A * 4/1998 teachet al. T19.316 6,182,062 B1 1/2001 Fujisawa et al. 5,751,928 A 5, 1998 Bakalash 6,189,004 B1 2/2001 Rassen et al. 576.1653 A 6, 1998 ty 6,199,063 B1 3/2001 Colby et al. 5,765.028 A 6/1998 Gladden 6,205,447 B1 3/2001 Malloy 5,767.854. A 6, 1998 Anwar 6,208.975 B1 3/2001 Bullet al. 5,781896 A * 7/1998 Dalai. 707,999.OO2 3.29. R 338 list et al. 5,794.228 A 8, 1998 French et al. 4 - 4 g 5,794.229 A 8, 1998 F h etal 6.212,524 B1 4/2001 Weissman et al. $752. A $56 S.E.5al 6,212,617 B1 4/2001 Hardwick 5,799,300 A 8/1998 Agrawal et al. 33: 38: Sea 5,805,885 A * 9/1998 Leach et al. .................. T19.316 6,226,647 Bi 52001 Venkatasu-b ian et al 5,822,751 A * 10/1998 Gray et al. ............. TO7/999.003 g; : Sriramanian et al. 5,832,475 A 11/1998 Agrawal et al. 6.256.676 B1 7/2001 Tavlor et all 5,848,424 A * 12/1998 Scheinkman et al. ........ 71.5/210 5688 756. E." 5,850,547 A 12/1998 Waddington et al. 4. WW 5,852.819. A 12, 1998 Bell 6,269,393 B1 7/2001 Yost et al. 5,852,821. A 2, 1998 Neal 6,275,818 B1 8/2001 Subramanian et al. 5,857,184 A : 1/1999 Lynch. TO7 (999-004 6,282,544 B1 8/2001 Tse et al. 5.864,857 A 1/1999 Ohata et all 6,282.546 B1 8, 2001 Gleichaufetal. 5,867,501. A 2, 1999 Horstet al. 6,285,994 B1 9/2001 Buiet al. 5.884.299 A 3, 1999 Ramesh et all 6,289,334 B1 9, 2001 Reiner et al. 5.890,151 A 3/1999 Agrawaletal. 333. 858 EY 5,890,154 A 3, 1999 Hsiao et al. - W - 5,901,287 A 5, 1999 Bulletal 6,317,750 B1 1 1/2001 Tortolani et al. 5,905,985 A 5, 1999 Rival 6,321,206 B1 * 1 1/2001 Honarvar ..................... 705/7.33 5915.257 A 6, 1999 &NR. 6,321.241 B1 1 1/2001 Gartung et al. 598.225 A 6, 1999 WE 6,324,533 B1 1 1/2001 Agrawal et al. 5,918,232 A 6/1999 Pouschine et al. 33 R 1858: R tein et al 5,926,818. A 7/1999 Malloy - - W eilersteinet al. 5926,820 A T. 1999 A letal 6,332,130 B1 12/2001 Notani et al. 5.937.410 A 8, 1999 Sawa Ca 6,339,775 B1 1/2002 Zamanian et al. 5.940.818 A 8/1999 Malloy etal 6,356,900 B1 3/2002 Egilsson et al.
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